code: def test_summary(df_daily):
      """Tests functionality on daily data."""
      df_train = df_daily["df_train"]
  
      model = LagBasedEstimator(
          lag_unit="day", lags=[2, 3], agg_func="median"
      )
      model.fit(df_train)
      summary = model.summary()
      assert (
          f"This is a lag based forecast model that uses lags '[2, 3]', "
          f"with unit 'day' and aggregation function"
      ) in summary
  
imports: from datetime import timedelta
  import numpy
  import pandas
  import pytest
  from dateutil.relativedelta import relativedelta
  from testfixtures import LogCapture
  from greykite.common.constants import ERR_STD_COL
  from greykite.common.constants import LOGGER_NAME
  from greykite.common.constants import PREDICTED_COL
  from greykite.common.constants import PREDICTED_LOWER_COL
  from greykite.common.constants import PREDICTED_UPPER_COL
  from greykite.sklearn.estimator.lag_based_estimator import LagBasedEstimator
label_desc: Use image node_id 17 for calling a global function with example usage: test_summary(df_daily) without return types